Deterministic models, even if used repeatedly, will not capture the essence of planning in an uncertain world. Flexibility and robustness can only be properly valued in models that use stochastics explicitly, such as stochastic optimization models. However, it may also be very important to...

Service network design under uncertainty is fundamentally crucial for all freight transportation companies. The main challenge is to strike a balance between two conflicting objectives: low network setup costs and low expected operational costs. Together these have a significant impact on the...

The purpose of this paper is to formally describe new optimization models for distributed telecommunication networks. Modern distributed networks put more focus on the processing of information and less on the actual transportation of data than we are traditionally used to in telecommunications....

Logistics problems are gradually becoming more complex and a better understanding of logistics management as a subject is a key to deal with the new challenges. A core element of logistics management is logistics planning, which substitutes for low customer service levels, high waste, and the...

Purpose – The value chain of the Norwegian meat production industry has recently been through major structural changes resulting in increased flows and transportation needs at all levels. The purpose of this paper is to present results of the initial stage of a five‐year research project...

Purpose – Discusses why it is necessary to align a mathematical model with the organization in order to achieve the desired results. The structure of a model's input must fit with the structure of data collection in the firm, and the output must be consistent with the decision structure....

Enterprise risk management is the discipline that governs the integrated management of the aggregate risks for a given firm with consideration for its strategic and organizational context. The authors present, in three installments, a case study on developing and implementing a stochastic...